code: def _load_from_state_dict(
      self,
      state_dict,
      prefix,
      local_metadata,
      strict,
      missing_keys,
      unexpected_keys,
      error_msgs,
  ):
      version = local_metadata.get("version", None)
  
      if version is None or version < 2:
          num_blocks = len(self)
          for i in range(num_blocks):
              for type in ["weight", "bias"]:
                  old_key = f"{prefix}mask_fcn{i+1}.{type}"
                  new_key = f"{prefix}{i}.0.{type}"
                  if old_key in state_dict:
                      state_dict[new_key] = state_dict.pop(old_key)
  
      super()._load_from_state_dict(
          state_dict,
          prefix,
          local_metadata,
          strict,
          missing_keys,
          unexpected_keys,
          error_msgs,
      )
  
imports: from collections import OrderedDict
  from typing import Any, Callable, Optional
  from torch import nn
  from torchvision.ops import MultiScaleRoIAlign
  from ...ops import misc
  from ...transforms._presets import ObjectDetection
  from .._api import register_model, Weights, WeightsEnum
  from .._meta import _COCO_CATEGORIES
  from .._utils import _ovewrite_value_param, handle_legacy_interface
  from ..resnet import resnet50, ResNet50_Weights
  from ._utils import overwrite_eps
  from .backbone_utils import _resnet_fpn_extractor, _validate_trainable_layers
  from .faster_rcnn import _default_anchorgen, FasterRCNN, FastRCNNConvFCHead, RPNHead
label_desc: Use image node_id 2 for calling the MaskRCNNHeads obj's underlying member method code with example usage: obj._load_from_state_dict(state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs) without return types